We know that due to multi-collinearity, the standard errors of beta estimates get inflated. But what is the mathematical basis to it?
I am looking for some mathematical relationship or something to explain this.
Like I understand if standard error of betas goes up, then t-statistics goes down and we might not be able to reject the null or the variables would appear non-significant.
But what is the mathematical relationship between multicolllinearity and inflation in variance of coefficients?